Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Accesses and queries the world's largest database of somatic mutations for cancer research and precision oncology applications.
Guides researchers through test selection, automated assumption checking, and APA-formatted statistical reporting.
Performs advanced RNA velocity analysis to infer cell state transitions and developmental trajectories from single-cell transcriptomics data.
Simplifies molecular cheminformatics and drug discovery workflows by providing a Pythonic interface to RDKit with sensible defaults.
Simulates and analyzes open quantum systems, master equations, and quantum optics dynamics using the QuTiP library.
Queries the Federal Reserve Economic Data (FRED) API to retrieve, analyze, and transform over 800,000 global economic indicators and time series.
Processes and manipulates DICOM medical imaging data including metadata extraction, pixel array processing, and automated anonymization.
Accesses the comprehensive BRENDA database to retrieve enzyme kinetic parameters, reaction equations, and biochemical data for metabolic analysis.
Performs real-time AI-powered web searches using Perplexity models to provide grounded answers with source citations.
Provides automated interpretability and explainability for machine learning models by analyzing feature importance and prediction logic.
Optimizes AI agent action spaces and tool definitions to improve task completion rates and error recovery.
Generates high-quality images, videos, and audio using fal.ai's state-of-the-art AI models directly through Claude Code.
Simplifies video and audio analysis, editing, and automation using AI-powered indexing and server-side processing.
Optimizes AI agent action spaces and tool definitions to maximize completion rates and system reliability.
Generates high-fidelity images, videos, and audio assets directly through the fal.ai MCP server.
Implements robust rate limiting and exponential backoff strategies for LangChain-based LLM applications.
Optimizes LLM API expenses through intelligent model routing, budget tracking, and efficient caching strategies.
Orchestrates complex social science research and systematic reviews using 24 specialized agents and integrated academic database tools.
Enables Claude to see, understand, search, and programmatically edit video and audio media through advanced indexing and timeline operations.
Standardizes meta-analysis data extraction through a multi-layered AI-human collaboration framework and automated statistical provenance.
Optimizes expensive file processing pipelines by caching results based on content identity rather than file paths.
Builds and deploys production-ready generative AI agents using Vertex AI, Gemini models, and Google Cloud infrastructure.
Optimizes LLM prompts to reduce token consumption, lower API costs, and improve response performance.
Builds autonomous AI agents capable of tool calling and multi-step decision-making using the LangChain framework.
Extracts and validates federated taxonomy tags from text to enable multi-hop graph traversal and structured memory storage.
Extracts structured data from complex PDFs, scanned documents, and multi-column layouts using the advanced Docling engine and Granite vision-language models.
Performs advanced econometric analysis including regression modeling, panel data estimation, and causal inference for economic and financial data.
Optimizes AI agent behavior using structured XML system prompts, few-shot examples, and clear instruction hierarchies.
Wipes all stored learning data and reinitializes the Claude Code Learning Memory System to its default state.
Designs and optimizes high-performance prompts to ensure LLM-powered applications follow instructions with precision and consistency.
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